Ribo-Pop – Simple, cost-effective, and widely applicable ribosomal RNA depletion

The measurement of RNA abundance derived from massively parallel sequencing experiments is an essential technique. Methods that reduce ribosomal RNA levels are usually required prior to sequencing library construction because ribosomal RNA typically comprises the vast majority of a total RNA sample. For some experiments, ribosomal RNA depletion is favored over poly(A) selection because it offers a more inclusive representation of the transcriptome. However, methods to deplete ribosomal RNA are generally proprietary, complex, inefficient, applicable to only specific species, or compatible with only a narrow range of RNA input levels.

Here, University of Oxford researchers describe Ribo-Pop (ribosomal RNA depletion for popular use), a simple workflow and antisense oligo design strategy that they demonstrate works over a wide input range and can be easily adapted to any organism with a sequenced genome. The researchers provide a computational pipeline for probe selection, a streamlined 20-minute protocol, and ready-to-use oligo sequences for several organisms. They anticipate that this simple and generalizable “open source” design strategy would enable virtually any lab to pursue full transcriptome sequencing in their organism of interest with minimal time and resource investment.

Outline of the single-probe depletion assay

rna-seq

A 3′ biotinylated probe targeting a specific site in the 18S is added to total RNA and subjected to hybridization. The target is captured with streptavidin beads and the remaining target is measured from the supernatant.

Availability – The pipeline is available at: https://github.com/marykthompson/ribopop_probe_design

Thompson MK, Kiourlappou M, Davis I. (2002) Ribo-Pop: Simple, cost-effective, and widely applicable ribosomal RNA depletion. RNA [published online ahead of print]. [article]

Leave a Reply

Your email address will not be published. Required fields are marked *

*

Time limit is exhausted. Please reload CAPTCHA.